亚马逊Senior Product Manager - AI, Amazon Global Selling - PMO

* Identify opportunities across the Global Selling Seller segments and lifecycle, define product strategy and proposition, build up new products/services to help seller growth and AM’s workflow optimization, and continuously drive product success post launch. * Clearly define and communicate product requirements, collaborate with and earn trust from internal stakeholders and external partners, and design and align system solutions. * Work with technology teams to develop products, resolve issues and manage development cycles * Manage stakeholder and leadership communications including problem statement and analysis, product solution review, business/impact review, budget/HC planning, stakeholder change management, etc.

Define AI product vision and strategy across Global Selling seller segments and lifecycle stages; identify high-impact opportunities to apply AI/ML (e.g., GenAI, agentic AI, intelligent automation) to empower business teams — including Marketing, CRM, seller acquisition, and seller growth — to drive operational efficiency and business outcomes at scale. Own the end-to-end AI product lifecycle — from ideation and opportunity sizing, through technical development and experimentation, to launch, adoption, and iterative improvement — ensuring alignment between business objectives, user needs, and technological capabilities. Develop and communicate product requirements including model objectives, data specifications, evaluation metrics, and responsible AI guardrails; earn trust from cross-functional stakeholders (engineering, applied science, design, business operations) and external partners through clear documentation and aligned decision-making. Lead cross-functional and cross-regional collaboration with scientists, engineering, and data teams to build, evaluate, and ship AI-powered products; drive development velocity by managing trade-offs, unblocking technical dependencies, resolving issues, and maintaining rigorous experimentation standards (A/B testing, model performance benchmarks). Drive measurable business impact post-launch through continuous monitoring, data-driven iteration, and feedback loops; leverage market analysis and competitive intelligence to inform product positioning and roadmap evolution. Manage stakeholder and leadership communications across multiple geographies — including problem framing, AI solution trade-off analysis, product/business reviews, budget and headcount planning, and organizational change management for AI adoption at scale. Partner with international stakeholders, leaders, and tech teams to align priorities and drive execution across regions.

Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams

Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions, develop AI applications for simple use cases through vibe-coding and Amazon AI tools. • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams